Machine-Aware Atomic Broadcast Trees for Multicores

نویسندگان

  • Stefan Kaestle
  • Reto Achermann
  • Roni Haecki
  • Moritz Hoffmann
  • Sabela Ramos
  • Timothy Roscoe
چکیده

The performance of parallel programs on multicore machines often critically depends on group communication operations like barriers and reductions being highly tuned to hardware, a task requiring considerable developer skill. Smelt is a library that automatically builds efficient inter-core broadcast trees tuned to individual machines, using a machine model derived from hardware registers plus micro-benchmarks capturing the low-level machine characteristics missing from vendor specifications. Experiments on a wide variety of multicore machines show that near-optimal tree topologies and communication patterns are highly machine-dependent, but can nevertheless be derived by Smelt and often further improve performance over well-known static topologies. Furthermore, we show that the broadcast trees built by Smelt can be the basis for complex group operations like global barriers or state machine replication, and that the hardware-tuning provided by the underlying tree is sufficient to deliver as good or better performance than stateof-the-art approaches: the higher-level operations require no further hardware optimization.

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تاریخ انتشار 2016